TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Yu Li; Xiaozhou Pan; Wenwei Luo; Yaser Gamalla; Zhan Ma; Pei Zhou; Chunfu Dai; Dingding Han

Heliyon (Jun 2024)

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Yu Li,
Xiaozhou Pan,
Wenwei Luo,
Yaser Gamalla,
Zhan Ma,
Pei Zhou,
Chunfu Dai,
Dingding Han

Affiliations

Yu Li: Department of Clinical Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; Institute of Pediatric Infection, Immunity, and Critical Care Medicine, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; College of Health Science and Technology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; Department of Otolaryngology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510000, China; Department of the Otology and Skull Base Surgery, Eye Ear Nose and Throat Hospital, Fudan University, Shanghai, 200031, China
Xiaozhou Pan: Department of Clinical Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; Institute of Pediatric Infection, Immunity, and Critical Care Medicine, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; College of Health Science and Technology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China
Wenwei Luo: Department of Otolaryngology-Head and Neck Surgery, Guangdong Provincial People's Hospital, Guang-dong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
Yaser Gamalla: Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, China; Department of Oncology, Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Alberta, T2N 4N1, Canada
Zhan Ma: Department of Clinical Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; Institute of Pediatric Infection, Immunity, and Critical Care Medicine, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; College of Health Science and Technology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China
Pei Zhou: Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, China; Corresponding author.
Chunfu Dai: Department of the Otology and Skull Base Surgery, Eye Ear Nose and Throat Hospital, Fudan University, Shanghai, 200031, China; Corresponding author.
Dingding Han: Department of Clinical Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; Institute of Pediatric Infection, Immunity, and Critical Care Medicine, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; College of Health Science and Technology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China; Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, China; Medical School, Guangxi University, Nanning, 530004, China; Corresponding author. Department of Clinical Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China.

Journal volume & issue: Vol. 10, no. 11
p. e31877

Abstract

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Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

Published in Heliyon

ISSN: 2405-8440 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Science (General); Social Sciences: Social sciences (General)
Website: https://www.cell.com/heliyon/home

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